Research Engineer, Production Model Post-Training, London at Anthropic

London, England, United Kingdom

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine LearningIndustries

Requirements

Proficiency in Python (all interviews conducted in Python)
Strong software engineering skills with experience building complex ML systems
Comfortable working with large-scale distributed systems and high-performance computing
Experience with training, fine-tuning, or evaluating large language models
At least a Bachelor's degree in a related field or equivalent experience
Ability to thrive in controlled chaos, juggle multiple urgent priorities, and adapt quickly to changing priorities
Maintain clarity when debugging complex, time-sensitive issues
Balance research exploration with engineering rigor and operational reliability
Adept at analyzing and debugging model training processes
Enjoy collaborating across research and engineering disciplines
Navigate ambiguity and make progress in fast-moving research environments
Availability to respond to incidents on short notice, including weekends

Responsibilities

Implement and optimize post-training techniques at scale on frontier models
Conduct research to develop and optimize post-training recipes that directly improve production model quality
Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
Develop tools to measure and improve model performance across various dimensions
Collaborate with research teams to translate emerging techniques into production-ready implementations
Debug complex issues in training pipelines and model behavior
Help establish best practices for reliable, reproducible model post-training

Skills

Python

Constitutional AI

RLHF

model fine-tuning

model evaluation

training pipelines

scaling

debugging

machine learning

Anthropic

Develops reliable and interpretable AI systems

About Anthropic

Anthropic focuses on creating reliable and interpretable AI systems. Its main product, Claude, serves as an AI assistant that can manage tasks for clients across various industries. Claude utilizes advanced techniques in natural language processing, reinforcement learning, and code generation to perform its functions effectively. What sets Anthropic apart from its competitors is its emphasis on making AI systems that are not only powerful but also understandable and controllable by users. The company's goal is to enhance operational efficiency and improve decision-making for its clients through the deployment and licensing of its AI technologies.

San Francisco, CaliforniaHeadquarters

2021Year Founded

$11,482.1MTotal Funding

GROWTH_EQUITY_VCCompany Stage

Enterprise Software, AI & Machine LearningIndustries

1,001-5,000Employees

Benefits

Flexible Work Hours

Paid Vacation

Parental Leave

Hybrid Work Options

Company Equity

Risks

Ongoing lawsuit with Concord Music Group could lead to financial liabilities.

Technological lag behind competitors like OpenAI may impact market position.

Reliance on substantial funding rounds may indicate financial instability.

Differentiation

Anthropic focuses on AI safety, contrasting with competitors' commercial priorities.

Claude, Anthropic's AI assistant, is designed for tasks of any scale.

Partnerships with tech giants like Panasonic and Amazon enhance Anthropic's strategic positioning.

Upsides

Anthropic's $60 billion valuation reflects strong investor confidence and growth potential.

Collaborations like the Umi app with Panasonic tap into the growing wellness AI market.

Focus on AI safety aligns with increasing industry emphasis on ethical AI development.

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